generative-ai
Sample code and notebooks for Generative AI on Google Cloud, with Gemini on Vertex AI
Star Growth
Overview
A comprehensive repository containing sample code, notebooks, and applications for building generative AI solutions on Google Cloud Platform using Vertex AI. This resource serves as the official collection of practical examples for Google's generative AI services, including the latest Gemini 3.1 Pro model, Imagen for computer vision tasks, and Vertex AI Search capabilities. The repository is organized into specialized sections covering different AI domains: Gemini for conversational AI and function calling, vision processing with Imagen, retrieval-augmented generation (RAG) implementations, and enterprise search solutions. With over 16,000 GitHub stars, it represents the go-to learning resource for developers working with Google's AI ecosystem. The content includes starter notebooks for beginners, advanced use cases, sample applications, and production-ready code patterns that demonstrate best practices for deploying generative AI workflows on Google Cloud infrastructure.
Deep Analysis
Google's official sample repository for Generative AI on Google Cloud — the most comprehensive collection of Gemini, Imagen, and Vertex AI notebooks, unlike third-party tutorials it's maintained by Google and always reflects latest APIs
⚡ Capabilities
- • Notebook samples for Google Cloud Generative AI
- • Gemini model tutorials and demos
- • Vertex AI Search integration examples
- • RAG and Grounding with Vertex AI
- • Image generation/editing with Imagen
- • Speech processing with Chirp/USM
- • Multi-modal AI application samples
🔗 Integrations
✓ Best For
- ✓ Learning Google Cloud's generative AI capabilities with hands-on examples
- ✓ Teams already on Google Cloud wanting to integrate Gemini/Vertex AI
✗ Not Ideal For
- ✗ Multi-cloud or provider-agnostic AI development
- ✗ Production applications (these are samples, not production code)
Languages
Deployment
Pricing Detail
⚠ Known Limitations
- ⚠ Google Cloud-specific — not provider-agnostic
- ⚠ Sample code, not a library/framework
- ⚠ Requires Google Cloud account and billing setup
- ⚠ Notebooks may become outdated as APIs evolve
Pros
- + Comprehensive coverage of Google Cloud's entire generative AI stack with practical, runnable examples
- + Regularly updated with latest models and features, including recent Gemini 3.1 Pro integration
- + High-quality, well-documented code samples that serve as production-ready starting points
Cons
- - Exclusively focused on Google Cloud Platform, limiting portability to other cloud providers
- - Requires Google Cloud account and potentially significant cloud costs for experimentation
- - Learning resource rather than a standalone tool, requiring additional setup and configuration
Use Cases
- • Learning and prototyping with Google Cloud's generative AI services like Gemini and Vertex AI
- • Building enterprise search solutions using Vertex AI Search for websites and internal data
- • Implementing computer vision applications with Imagen for image generation, editing, and analysis